Digital image correlation and finite element modelling as a method to determine mechanical properties of human soft tissue in vivo

TL;DR

This study explores combining Digital Image Correlation (DIC) with finite element modeling to non-invasively determine the mechanical properties of human soft tissue in vivo, validated through experiments on a silicone gel phantom.

Contribution

It introduces a novel approach using DIC with FE modeling for soft tissue property estimation, simplifying the process compared to traditional MRI-based methods.

Findings

DIC effectively captured 3D surface deformation data.

FE simulations matched experimental indentation results.

Method shows promise for non-invasive tissue property assessment.

Abstract

The mechanical properties of human soft tissue are crucial for impact biomechanics, rehabilitation engineering and surgical simulation. Validation of these constitutive models using human data remains challenging and often requires the use of non-invasive imaging and inverse finite element (FE) analysis. Post processing data from imaging methods such as tagged magnetic resonance imaging (MRI) can be challenging. Digital Image Correlation (DIC) however is a relatively straightforward imaging method and thus the goal of this study was to assess the use of DIC in combination with FE modelling to determine the bulk material properties of human soft tissue. Indentation experiments were performed on a silicone gel soft tissue phantom. A two camera DIC setup was then used to record the 3D surface deformation. The experiment was then simulated using a FE model.